Day ahead scheduling of generation and storage sources in a microgrid using artificial fish swarm algorithm

Abstract

Non-consistency of energy availability from Renewable Energy Sources needs estimation and scheduling in advance so that the other certain sources of energy like fuel cells, diesel generators, storage devices etc., can be scheduled appropriately to maintain load-generation balance in real time. Evolutionary program techniques are proving handy and reliable in the process. This article uses an Artificial Fish Swarm algorithm to solve the problem of day-ahead scheduling of generation in a mix of Renewable Energy Sources, despatchable sources and storage. The utility function of hourly generation cost is considered for optimization along with various microgrid operational constraints. The performance of the algorithm is validated by applying to schedule generation in a microgrid in grid connected mode consisting of one wind turbine and one PV source as Renewable energy sources, one diesel generator and fuel cell as despatchable generators and a battery for storage. The scheduled generation of each generator, power exchange of storage source along with its state of charge are evaluated for optimum cost of generation.